3 accepted papers
Camera-based Semantic Scene Completion (SSC) is able to comprehensively understand the entire scene, but it suffers from ambiguous predictions due to occlusions and incomplete information. Temporal SSC alleviates this issue, but existing models simply stack multi-frame temporal features, which can l
Vision-based semantic scene completion (SSC) is able to predict complex scene information from limited 2D images, which has attracted widespread attention. Currently, SSC methods typically construct unified voxel features containing both geometry and semantics, which lead to different depth position…
Camera-based Semantic Scene Completion (SSC) is to infer the full geometry of objects and scenes from only 2D images. The task is particularly challenging for those invisible areas due to the inherent occlusions and lighting ambiguity. Existing works ignore the information missing or ambiguous in th…